Job search engine with 500k+ listings across Austria, Germany and Switzerland (alleskralle.com).
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 4.6/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: search_jobs retrieves a list of job listings, while fetch_job returns detailed information for a specific job by ID. There is no overlap.
Both tool names follow a consistent verb_noun pattern: search_jobs and fetch_job, which is clear and predictable.
With only 2 tools, the server is minimal but still covers the core search and detail retrieval workflow. However, it feels thin for a job search domain that could benefit from additional filtering or categorization tools.
The tool set provides the essential search and detail retrieval functionality. A minor gap is the lack of explicit search parameters in search_jobs (e.g., keyword, location), but the overall flow is complete for basic use.
fetch_jobAInspectLiefert die vollständigen Details zu einer Stellenanzeige anhand ihrer id (aus search_jobs). Das Feld apply_url ist der Bewerbungslink zur Original-Anzeige. WICHTIG: apply_url NICHT selbst aufrufen oder abrufen — gib den Link dem Nutzer als anklickbaren Link aus, damit er sich bei Interesse selbst bewirbt bzw. die vollständige Anzeige öffnet.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Die id eines Treffers aus search_jobs. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description adds important context: it is a fetch operation, and it warns about not invoking the apply_url. This covers key behavioral aspects, though read-only nature is implied rather than explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences: first states purpose, second notes an important field, third gives a critical warning. No fluff, information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With one parameter, no annotations, and no output schema, the description covers the essential purpose and usage caution. It could briefly list key return fields, but the current level is functional and adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'id' is sufficiently described in the schema (100% coverage). The description only repeats that it comes from search_jobs, adding no new semantic value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns complete details of a job posting by id, referencing the sibling tool search_jobs as the source of the id. It differentiates itself by focusing on fetching a single record.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (with id from search_jobs) and includes a crucial instruction not to call apply_url directly but to provide it as a clickable link. This provides clear behavioral guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_jobsAInspectSucht Stellenanzeigen auf alleskralle.com (DE/AT/CH) und liefert eine kompakte Liste (id, title, company, location, date). Die Bewerbungs-/Detail-URL ist NICHT in der Liste enthalten — für vollständige Details und den klickbaren Link rufe fetch_job mit der id auf. Hinweis: "remote" ist eine Volltext-Heuristik (kein strukturiertes Feld), kann also ungenau sein. Blättern nur über das zurückgegebene next_cursor möglich; die Seitenzahl ist begrenzt.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Suchbegriff (Jobtitel, Tätigkeit, Skill). | |
| cursor | No | next_cursor aus einer vorherigen Antwort, um die nächste Seite zu laden. | |
| remote | No | Auf Remote-/Homeoffice-Stellen einschränken (Heuristik). | |
| country | No | Strikt auf ein Land einschränken: AT (Österreich), DE (Deutschland) oder CH (Schweiz). Kombinierbar mit location. | |
| location | No | Ort, Stadt oder PLZ. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses search scope, return format, missing detail URL, heuristic nature of 'remote', and pagination limitations. However, it does not mention authorization or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff, front-loaded with purpose. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters, no output schema, and a sibling tool, the description is thorough: it explains return fields, limitations, pagination, and relationship to fetch_job. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, baseline 3. The description adds value by explaining that 'remote' is a heuristic and that cursor is for pagination. It reinforces parameter context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches job listings on alleskralle.com (DE/AT/CH) and returns a compact list with id, title, company, location, and date. It distinguishes from the sibling tool fetch_job by noting that detail URLs are not included.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that for full details the user should call fetch_job with the id, warns that the 'remote' parameter is a heuristic, and notes that pagination is via next_cursor with limited pages. This provides explicit guidance on when and how to use the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
No comments yet. Be the first to start the discussion!
